SOTAVerified

Speech Recognition

Speech Recognition is the task of converting spoken language into text. It involves recognizing the words spoken in an audio recording and transcribing them into a written format. The goal is to accurately transcribe the speech in real-time or from recorded audio, taking into account factors such as accents, speaking speed, and background noise.

( Image credit: SpecAugment )

Papers

Showing 63516400 of 6433 papers

TitleStatusHype
The InproTK 2012 release0
Up from Limited Dialog Systems!0
HRItk: The Human-Robot Interaction ToolKit Rapid Development of Speech-Centric Interactive Systems in ROS0
Intra-Speaker Topic Modeling for Improved Multi-Party Meeting Summarization with Integrated Random Walk0
Unsupervised Vocabulary Adaptation for Morph-based Language Models0
Deep Neural Network Language Models0
A belief tracking challenge task for spoken dialog systems0
Implicitly Intersecting Weighted Automata using Dual Decomposition0
Real-time Incremental Speech-to-Speech Translation of Dialogs0
Exploring Content Features for Automated Speech Scoring0
A Challenge Set for Advancing Language Modeling0
Using Ontology-based Approaches to Representing Speech Transcripts for Automated Speech Scoring0
The IWSLT 2011 Evaluation Campaign on Automatic Talk Translation0
BUCEADOR, a multi-language search engine for digital libraries0
Building a 70 billion word corpus of English from ClueWeb0
Leveraging study of robustness and portability of spoken language understanding systems across languages and domains: the PORTMEDIA corpora0
The KIT Lecture Corpus for Speech Translation0
Rapidly Testing the Interaction Model of a Pronunciation Training System via Wizard-of-Oz0
Simplified guidelines for the creation of Large Scale Dialectal Arabic Annotations0
LDC Forced Aligner0
The DISCO ASR-based CALL system: practicing L2 oral skills and beyond0
Prosomarker: a prosodic analysis tool based on optimal pitch stylization and automatic syllabi fication0
The META-SHARE Language Resources Sharing Infrastructure: Principles, Challenges, Solutions0
Development of Text and Speech database for Hindi and Indian English specific to Mobile Communication environment0
Resource Evaluation for Usable Speech Interfaces: Utilizing Human-Human Dialogue0
Using an ASR database to design a pronunciation evaluation system in Basque0
A Mandarin-English Code-Switching Corpus0
A hierarchical approach with feature selection for emotion recognition from speech0
Building Text-To-Speech Voices in the Cloud0
RWTH-PHOENIX-Weather: A Large Vocabulary Sign Language Recognition and Translation Corpus0
Dysarthric Speech Database for Development of QoLT Software Technology0
Suffix Trees as Language Models0
Building a synchronous corpus of acoustic and 3D facial marker data for adaptive audio-visual speech synthesis0
Syntactic annotation of spontaneous speech: application to call-center conversation data0
A Scalable Architecture For Web Deployment of Spoken Dialogue Systems0
Item Development and Scoring for Japanese Oral Proficiency Testing0
Evaluating Appropriateness Of System Responses In A Spoken CALL Game0
Holaaa!! writin like u talk is kewl but kinda hard 4 NLP0
Constructive Interaction for Talking about Interesting Topics0
A Corpus for a Gesture-Controlled Mobile Spoken Dialogue System0
CoALT: A Software for Comparing Automatic Labelling Tools0
TED-LIUM: an Automatic Speech Recognition dedicated corpus0
Multimodal Corpus of Multi-party Conversations in Second Language0
Korean Children's Spoken English Corpus and an Analysis of its Pronunciation Variability0
Cross-lingual studies of ASR errors: paradigms for perceptual evaluations0
The Herme Database of Spontaneous Multimodal Human-Robot Dialogues0
From keystrokes to annotated process data: Enriching the output of Inputlog with linguistic information0
DECODA: a call-centre human-human spoken conversation corpus0
Statistical Evaluation of Pronunciation Encoding0
The Twins Corpus of Museum Visitor Questions0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AmNetWord Error Rate (WER)8.6Unverified
2HMM-(SAT)GMMWord Error Rate (WER)8Unverified
3Local Prior Matching (Large Model)Word Error Rate (WER)7.19Unverified
4SnipsWord Error Rate (WER)6.4Unverified
5Li-GRUWord Error Rate (WER)6.2Unverified
6HMM-DNN + pNorm*Word Error Rate (WER)5.5Unverified
7CTC + policy learningWord Error Rate (WER)5.42Unverified
8Deep Speech 2Word Error Rate (WER)5.33Unverified
9HMM-TDNN + iVectorsWord Error Rate (WER)4.8Unverified
10Gated ConvNetsWord Error Rate (WER)4.8Unverified
#ModelMetricClaimedVerifiedStatus
1Local Prior Matching (Large Model)Word Error Rate (WER)20.84Unverified
2SnipsWord Error Rate (WER)16.5Unverified
3Local Prior Matching (Large Model, ConvLM LM)Word Error Rate (WER)15.28Unverified
4Deep Speech 2Word Error Rate (WER)13.25Unverified
5TDNN + pNorm + speed up/down speechWord Error Rate (WER)12.5Unverified
6CTC-CRF 4gram-LMWord Error Rate (WER)10.65Unverified
7Convolutional Speech RecognitionWord Error Rate (WER)10.47Unverified
8MT4SSLWord Error Rate (WER)9.6Unverified
9Jasper DR 10x5Word Error Rate (WER)8.79Unverified
10EspressoWord Error Rate (WER)8.7Unverified
#ModelMetricClaimedVerifiedStatus
1Deep SpeechPercentage error20Unverified
2DNN-HMMPercentage error18.5Unverified
3CD-DNNPercentage error16.1Unverified
4DNNPercentage error16Unverified
5DNN + DropoutPercentage error15Unverified
6DNN BMMIPercentage error12.9Unverified
7DNN MPEPercentage error12.9Unverified
8DNN MMIPercentage error12.9Unverified
9HMM-TDNN + pNorm + speed up/down speechPercentage error12.9Unverified
10HMM-DNN +sMBRPercentage error12.6Unverified
#ModelMetricClaimedVerifiedStatus
1LSNNPercentage error33.2Unverified
2LAS multitask with indicators samplingPercentage error20.4Unverified
3Soft Monotonic Attention (ours, offline)Percentage error20.1Unverified
4QCNN-10L-256FMPercentage error19.64Unverified
5Bi-LSTM + skip connections w/ CTCPercentage error17.7Unverified
6Bi-RNN + AttentionPercentage error17.6Unverified
7RNN-CRF on 24(x3) MFSCPercentage error17.3Unverified
8CNN in time and frequency + dropout, 17.6% w/o dropoutPercentage error16.7Unverified
9Light Gated Recurrent UnitsPercentage error16.7Unverified
10GRUPercentage error16.6Unverified
#ModelMetricClaimedVerifiedStatus
1AttWord Error Rate (WER)18.7Unverified
2CTC/AttWord Error Rate (WER)6.7Unverified
3BRA-EWord Error Rate (WER)6.63Unverified
4CTC-CRF 4gram-LMWord Error Rate (WER)6.34Unverified
5BATWord Error Rate (WER)4.97Unverified
6ParaformerWord Error Rate (WER)4.95Unverified
7U2Word Error Rate (WER)4.72Unverified
8UMAWord Error Rate (WER)4.7Unverified
9Lightweight TransducerWord Error Rate (WER)4.31Unverified
10CIF-HKD With LMWord Error Rate (WER)4.1Unverified
#ModelMetricClaimedVerifiedStatus
1Jasper 10x3Word Error Rate (WER)6.9Unverified
2CNN over RAW speech (wav)Word Error Rate (WER)5.6Unverified
3CTC-CRF 4gram-LMWord Error Rate (WER)3.79Unverified
4Deep Speech 2Word Error Rate (WER)3.6Unverified
5test-set on open vocabulary (i.e. harder), model = HMM-DNN + pNorm*Word Error Rate (WER)3.6Unverified
6Convolutional Speech RecognitionWord Error Rate (WER)3.5Unverified
7TC-DNN-BLSTM-DNNWord Error Rate (WER)3.5Unverified
8EspressoWord Error Rate (WER)3.4Unverified
9CTC-CRF VGG-BLSTMWord Error Rate (WER)3.2Unverified
10Transformer with Relaxed AttentionWord Error Rate (WER)3.19Unverified